Context unification is in PSPACE

Contexts are terms with one `hole', i.e. a place in which we can substitute an argument. In context unification we are given an equation over terms with variables representing contexts and ask about the satisfiability of this equation. Context unification is a natural subvariant of second-order unification, which is undecidable, and a generalization of word equations, which are decidable, at the same time. It is the unique problem between those two whose decidability is uncertain (for already almost two decades). In this paper we show that the context unification is in PSPACE. The result holds under a (usual) assumption that the first-order signature is finite. This result is obtained by an extension of the recompression technique, recently developed by the author and used in particular to obtain a new PSPACE algorithm for satisfiability of word equations, to context unification. The recompression is based on performing simple compression rules (replacing pairs of neighbouring function symbols), which are (conceptually) applied on the solution of the context equation and modifying the equation in a way so that such compression steps can be in fact performed directly on the equation, without the knowledge of the actual solution.Comment: 27 pages, submitted, small notation changes and small improvements over the previous tex

Minimizing finite automata is computationally hard

It is known that deterministic finite automata (DFAs) can be algorithmically minimized, i.e., a DFA M can be converted to an equivalent DFA M' which has a minimal number of states. The minimization can be done efficiently [6]. On the other hand, it is known that unambiguous finite automata (UFAs) and nondeterministic finite automata (NFAs) can be algorithmically minimized too, but their minimization problems turn out to be NP-complete and PSPACE-complete [8]. In this paper, the time complexity of the minimization problem for two restricted types of finite automata is investigated. These automata are nearly deterministic, since they only allow a small amount of non determinism to be used. On the one hand, NFAs with a fixed finite branching are studied, i.e., the number of nondeterministic moves within every accepting computation is bounded by a fixed finite number. On the other hand, finite automata are investigated which are essentially deterministic except that there is a fixed number of different initial states which can be chosen nondeterministically. The main result is that the minimization problems for these models are computationally hard, namely NP-complete. Hence, even the slightest extension of the deterministic model towards a nondeterministic one, e.g., allowing at most one nondeterministic move in every accepting computation or allowing two initial states instead of one, results in computationally intractable minimization problems

On the Limits of Second-Order Unification

Second-Order Unification is a problem that naturally arises when applying automated deduction techniques with variables denoting predicates. The problem is undecidable, but a considerable effort has been made in order to find decidable fragments, and understand the deep reasons of its complexity. Two variants of the problem, Bounded Second-Order Unification and Linear Second-Order Unification ¿where the use of bound variables in the instantiations is restricted¿, have been extensively studied in the last two decades. In this paper we summarize some decidability/undecidability/complexity results, trying to focus on those that could be more interesting for a wider audience, and involving less technical details.Peer Reviewe

ML with PTIME complexity guarantees

Implicit Computational Complexity is a line of research where the possibility to inference a valid property for a program implies that the program runs in particular complexity class. Soft type systems are one of the research threads within the field. We present here a soft type system with ML-like polymorphism that enjoys decidable typechecking, type inference and typability problems and gives polynomial time computational guarantees for the running time of typed programs

Towards Deciding Second-order Unification Problems Using Regular Tree Automata

International audienceThe second-order unification problem is undecidable [5]. While unification procedures, like Huet's pre-unification, terminate with success on unifiable problems, they might not terminate on non-unifiable ones. There are several decidability results for unification problems with infinitely-many pre-unifiers, such as for monadic second-order problems [3]. These results are based on the regular structure of the solutions of these problems and by computing minimal unifiers. Beyond the importance of the knowledge that searching for unifiers of decidable problems always terminates, one can also use this information in order to optimize unification algorithms, such as in the case for pattern unification [10]. Nevertheless, being able to prove that the unification problem of a certain class of unification constraints is decidable is far from easy. Some results were obtained for certain syntactic restrictions on the problems (see Levy [8] for some results and references) or on the unifiers (see Schmidt-Schauß [11], Schmidt-Schauß and Schulz [12, 13] and Je˙ z [7] for some results). Infinitary unification problems, like the ones we are considering, might suggest that known tools for dealing with the infinite might be useful. One such tool is the regular tree automaton. The drawback of using regular automata for unification is, of course, their inability to deal with variables. In this paper we try to overcome this obstacle and describe an ongoing work about using regular tree automata [1] in order to decide more general second-order unification problems. The second-order unification problems we will consider are of the form λz n .x 0 t. = λz n .C(x 0 s) where C is a non-empty context [2] and x 0 does not occur in t or s. We will call such problems cyclic problems. An important result in second-order unification was obtained by Ganzinger et al. [4] and stated that second-order unification is undecidable already when there is only one second-order variable occurring twice. The unification problem they used for proving the undecidability result was an instance of the following cyclic problem. Note that we chose to use in the definition only unary second-order variables but that this restriction should not be essential. x 0 (w 1 , g(y 1 , a)) = g(y 2 , x 0 (w 2 , a)) (1) Our decidability result is obtained by posing one further restriction over cyclic problems which is based on the existence and location of variables other than the cyclic one. A sufficient condition for the decidability of second-order unification problems was given by Levy [8]. This condition states that if we can never encounter, when applying Huet's pre-unification procedure [6] to a problem, a cyclic equation, then the procedure terminates. It follows from this result that deciding second-order unification problems depends on the ability to decide cyclic problems. The rules of Huet's procedure (PUA) are given in Fig. 1. Imitation partial bindings and projection partial bindings are defined in [14] and are denoted, respectively, by PB(f, α) and PB(i, α) where α is a type, Σ a signature f ∈ Σ and i > 0

Logic Programming and Logarithmic Space

We present an algebraic view on logic programming, related to proof theory and more specifically linear logic and geometry of interaction. Within this construction, a characterization of logspace (deterministic and non-deterministic) computation is given via a synctactic restriction, using an encoding of words that derives from proof theory. We show that the acceptance of a word by an observation (the counterpart of a program in the encoding) can be decided within logarithmic space, by reducing this problem to the acyclicity of a graph. We show moreover that observations are as expressive as two-ways multi-heads finite automata, a kind of pointer machines that is a standard model of logarithmic space computation

Taming Strategy Logic: Non-Recurrent Fragments

Strategy Logic (SL for short) is one of the prominent languages for reasoning about the strategic abilities of agents in a multi-agent setting. This logic extends LTL with first-order quantifiers over the agent strategies and encompasses other formalisms, such as ATL* and CTL*. The model-checking problem for SL and several of its fragments have been extensively studied. On the other hand, the picture is much less clear on the satisfiability front, where the problem is undecidable for the full logic. In this work, we study two fragments of One-Goal SL, where the nesting of sentences within temporal operators is constrained. We show that the satisfiability problem for these logics, and for the corresponding fragments of ATL* and CTL*, is ExpSpace and PSpace-complete, respectively

Well-nested Context Unification

International audienceContext unification (CU) is the famous open problem of solving context equations for trees. We distinguish a new decidable fragment of CU - well-nested CU - and present a new unification algorithm that solves well-nested context equations in non-deterministic polynomial time. We show that minimal well-nested solutions of context equations can be composed from the material present in the equation. This surprising property is highly wishful when modeling natural language ellipsis in CU